Comparison of the Variance of Minimum Variance and Weighted Least Squares Regression Coefficients
نویسندگان
چکیده
منابع مشابه
Fast algorithms for least-squares-based minimum variance spectral estimation
The minimum variance (MV) spectral estimator is a robust high-resolution frequencydomain analysis tool for short data records. The traditional formulation of the minimum variance spectral estimation (MVSE) depends on the inverse of a Toeplitz autocorrelation matrix, for which a fast computational algorithm exists that exploits this structure. This paper extends the MVSE approach to two data-onl...
متن کاملLeast-squares variance component estimation
Least-squares variance component estimation (LS-VCE) is a simple, flexible and attractive method for the estimation of unknown variance and covariance components. LS-VCE is simple because it is based on the well-known principle of LS; it is flexible because it works with a userdefined weight matrix; and it is attractive because it allows one to directly apply the existing body of knowledge of L...
متن کاملConsistency for Least Squares Regression Estimators with Infinite Variance Data
The least squares estimators are discussed for the linear regression model with random predictors. Both predictors and errors may have infinite variance. Under the condition that the predictors are in a stable domain of attraction, we determine necessary and sufficient conditions for weak consistency of the least squares estimators in the simple linear model. The conditions vary, depending on w...
متن کاملEstimating residual variance in nonparametric regression using least squares
We propose a new estimator for the error variance in a nonparametric regression model. We estimate the error variance as the intercept in a simple linear regression model with squared differences of paired observations as the dependent variable and squared distances between the paired covariates as the regressor. Our method can be applied to nonparametric regression models with multivariate fun...
متن کاملRetrieving Three Dimensional Displacements of InSAR Through Regularized Least Squares Variance Component Estimation
Measuring the 3D displacement fields provide essential information regarding the Earth crust interaction and the mantle rheology. The interferometric synthetic aperture radar (InSAR) has an appropriate capability in revealing the displacements of the Earth’s crust. Although, it measures the real 3D displacements in the line of sight (LOS) direction. The 3D displacement vectors can be retrieved ...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: The Annals of Mathematical Statistics
سال: 1963
ISSN: 0003-4851
DOI: 10.1214/aoms/1177704021